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About

Evangelia Kavakli is a leading researcher in data-driven manufacturing, with a focus on harnessing big data analytics to optimize industrial production. Her work addresses the critical challenge of transforming unstructured, noisy, and incomplete data from complex production lines—comprising numerous robots and digital tools—into structured, actionable insights. Through her highly cited study on the Centro Ricerche FIAT (CRF) case, Kavakli provides essential guidelines and lessons learned for implementing big data analytics in the manufacturing sector, bridging the gap between raw data generation and meaningful process improvement. Her contributions have significant implications for Industry 4.0, enabling smarter, more efficient factories. With her research gaining traction among both academics and practitioners, Kavakli is establishing herself as a key voice in the practical application of data science to real-world manufacturing challenges, helping to shape the future of intelligent production systems.